CEA-List's CAD framework for designing and simulating Deep Neural Network, and building full DNN-based applications on embedded platforms.
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Llama3 implementation one matrix multiplication at a time.
A Natural Adversarial Language Processing framework built over Tensorflow.
General natural language facilities for node.
Semantic search and workflows powered by language models.
Code samples for my book "Neural Networks and Deep Learning" [DEEP LEARNING].
A PyTorch implementation of DeepDream.
A parallel neural net microframework.
A PyTorch implementation of Justin Johnson's neural-style (neural style transfer).
Natural Language processing in the browser.
An NLP library built in node over Natural, with entity extraction, sentiment analysis, automatic language identify, and so more.
A Julia package for non-negative matrix factorization.
Nn builder is a python package that lets you build neural networks in 1 line.
This package provides graphical computation for nn library in Torch7.
A completely unstable and experimental package that extends Torch's builtin nn library.
Support Vector Machine for Node.js.
Serve Llama 2 and other large language models locally from command line or through a browser interface.
Fujitsu Research's post-training quantization pipeline for LLMs (QEP, AutoBit, JointQ, rotation) with vLLM plugin (arXiv:2603.28845).
Compiler technology to transform a valid Open Neural Network Exchange (ONNX) graph into code that implements the graph with minimum runtime support.
An ONNX (Open Neural Network eXchange) API and backend for typeful, functional deep learning in Scala (3).
A library that enables training PyTorch models with differential privacy.
A list of open LLMs available for commercial use.
Open platform for operating large language models (LLMs) in production. Fine-tune, serve, deploy, and monitor any LLMs with ease.
A PyTorch-based framework to train and validate the models producing high-quality embeddings.